Interferon Regulatory Factor 7 Functions as a Novel Negative Regulator of Pathological Cardiac Hypertrophy
Bibliographic record
Abstract
Cardiac hypertrophy is a complex pathological process that involves multiple factors including inflammation and apoptosis. Interferon regulatory factor 7 (IRF7) is a multifunctional regulator that participates in immune regulation, cell differentiation, apoptosis, and oncogenesis. However, the role of IRF7 in cardiac hypertrophy remains unclear. We performed aortic banding in cardiac-specific IRF7 transgenic mice, IRF7 knockout mice, and the wild-type littermates of these mice. Our results demonstrated that IRF7 was downregulated in aortic banding-induced animal hearts and cardiomyocytes that had been treated with angiotensin II or phenylephrine for 48 hours. Accordingly, heart-specific overexpression of IRF7 significantly attenuated pressure overload-induced cardiac hypertrophy, fibrosis, and dysfunction, whereas loss of IRF7 led to opposite effects. Moreover, IRF7 protected against angiotensin II-induced cardiomyocyte hypertrophy in vitro. Mechanistically, we identified that IRF7-dependent cardioprotection was mediated through IRF7 binding to inhibitor of κB kinase-β, and subsequent nuclear factor-κB inactivation. In fact, blocking nuclear factor-κB signaling with cardiac-specific inhibitors of κBα(S32A/S36A) super-repressor transgene counteracted the adverse effect of IRF7 deficiency. Conversely, activation of nuclear factor-κB signaling via a cardiac-specific conditional inhibitor of κB kinase-β(S177E/S181E) (constitutively active) transgene negated the antihypertrophic effect of IRF7 overexpression. Our data demonstrate that IRF7 acts as a novel negative regulator of pathological cardiac hypertrophy by inhibiting nuclear factor-κB signaling and may constitute a potential therapeutic target for pathological cardiac hypertrophy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".